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This paper addresses the logical inconsistency of large language models (LLMs) in the context of complex fact-checking tasks using propositional logic queries. The authors introduce three logical fact-checking datasets and propose measures to assess the consistency of LLMs, demonstrating that existing models often lack logical consistency, especially with complex queries. They also present a method for improving LLM consistency through supervised fine-tuning, achieving an average improvement of 14% in consi

Author

abinrajlalraj165

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EN